Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

SuperEar: Eavesdropping on Mobile Voice Calls via Stealthy Acoustic Metamaterials

Zhiyuan Ning, Zhanyong Tang, Juan He, Weizhi Meng, Yuntian Chen, Ji Zhang, Zheng Wang

TL;DR

This work presents SuperEar, a portable acoustic eavesdropping system that leverages passive acoustic metamaterials to reliably intercept conversations from moving targets outdoors. By combining low-frequency gain via Mie resonators, spectrum-cropping and stitching across eight metamaterial units, and a distortion/noise suppression pipeline, the authors achieve over $80\%$ success up to $4.6 \text{ m}$, significantly extending prior eavesdropping ranges. The approach uses off-the-shelf hardware and 3D-printed components, with a Raspberry Pi performing beamforming, MVDR, and processing, underscoring a realistic privacy threat that warrants attention and defense. Practical implications include new considerations for acoustic side-channel security, potential countermeasures, and policy emphasis on protecting private speech leakage in public spaces. The results demonstrate robust performance across languages, various devices, weather conditions, and moving targets, revealing a tangible threat in everyday environments.

Abstract

Acoustic eavesdropping is a privacy risk, but existing attacks rarely work in real outdoor situations where people make phone calls on the move. We present SuperEar, the first portable system that uses acoustic metamaterials to reliably capture conversations in these scenarios. We show that the threat is real as a practical prototype can be implemented to enhance faint signals, cover the full range of speech with a compact design, and reduce noise and distortion to produce clear audio. We show that SuperEar can be implemented from low-cost 3D-printed parts and off-the-shelf hardware. Experimental results show that SuperEar can recover phone call audio with a success rate of over 80% at distances of up to 4.6 m - more than twice the range of previous approaches. Our findings highlight a new class of privacy threats enabled by metamaterial technology that requires attention.

SuperEar: Eavesdropping on Mobile Voice Calls via Stealthy Acoustic Metamaterials

TL;DR

This work presents SuperEar, a portable acoustic eavesdropping system that leverages passive acoustic metamaterials to reliably intercept conversations from moving targets outdoors. By combining low-frequency gain via Mie resonators, spectrum-cropping and stitching across eight metamaterial units, and a distortion/noise suppression pipeline, the authors achieve over success up to , significantly extending prior eavesdropping ranges. The approach uses off-the-shelf hardware and 3D-printed components, with a Raspberry Pi performing beamforming, MVDR, and processing, underscoring a realistic privacy threat that warrants attention and defense. Practical implications include new considerations for acoustic side-channel security, potential countermeasures, and policy emphasis on protecting private speech leakage in public spaces. The results demonstrate robust performance across languages, various devices, weather conditions, and moving targets, revealing a tangible threat in everyday environments.

Abstract

Acoustic eavesdropping is a privacy risk, but existing attacks rarely work in real outdoor situations where people make phone calls on the move. We present SuperEar, the first portable system that uses acoustic metamaterials to reliably capture conversations in these scenarios. We show that the threat is real as a practical prototype can be implemented to enhance faint signals, cover the full range of speech with a compact design, and reduce noise and distortion to produce clear audio. We show that SuperEar can be implemented from low-cost 3D-printed parts and off-the-shelf hardware. Experimental results show that SuperEar can recover phone call audio with a success rate of over 80% at distances of up to 4.6 m - more than twice the range of previous approaches. Our findings highlight a new class of privacy threats enabled by metamaterial technology that requires attention.
Paper Structure (45 sections, 4 equations, 20 figures, 3 tables)

This paper contains 45 sections, 4 equations, 20 figures, 3 tables.

Table of Contents

  1. INTRODUCTION
  2. Background and Related Work
  3. Acoustic Eavesdropping Attacks
  4. Outdoor Eavesdropping on Voice Output
  5. Acoustic Metamaterials
  6. Threat Model
  7. Methodology
  8. Overview of SuperEar
  9. Technical Challenges
  10. Enhancing the Gain of Low-frequency Signal
  11. Expanding bandwidth via multi-metamaterials
  12. Defining the gain range
  13. Determining the number of units.
  14. Spectrum cropping and stitching.
  15. Mitigating distortion and noise from metamaterial defects
  16. ...and 30 more sections

Figures (20)

  • Figure 1: (a) Possible attack: SuperEar eavesdrops on an outdoor call. (b) Call voice vs. other scenarios.
  • Figure 2: SuperEar eavesdropping overview: enhanced low-frequency narrowband signals (Sec. \ref{['chap:6.1']}), wideband amplification via multi-metamaterials (Sec. \ref{['chap:6.2']}), and defect-induced distortion/noise suppression (Sec. \ref{['chap:6.3']}).
  • Figure 3: (a) Acoustic metamaterial structure with a microphone at the center. (b) Metamaterial system.
  • Figure 4: (a) D and a individually. (b) D and a simultaneously. (c) Top: $k$ vs. D; Bottom: resonant frequency vs. bandwidth.
  • Figure 5: Optimal Number of Metamaterials
  • ...and 15 more figures